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Lead Software Engineer – AIML Data Platform (Data, Python, Containers/Kubernetes)

ExperiencedNo visa sponsorship
J.P. Morgan logo

at J.P. Morgan

Bulge Bracket Investment Banks

Posted 11 days ago

No clicks

**Lead Software Engineer - AIML Data Platform:** Lead agile team, enhancing secure, scalable technology products. Core responsibility: design, develop, and troubleshoot AI for Data solutions using Python. Utilize containers/Kubernetes, improve code quality, drive automation, and coach junior engineers. Requires advanced Python skills, hands-on experience in SDLC, and proficiency in cloud native environments, with a plus for graph database and Gen AI Engineering backgrounds.

Compensation
Not specified

Currency: Not specified

City
London
Country
United Kingdom

Full Job Description

Location: LONDON, LONDON, United Kingdom

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. 

As a Lead Software Engineer at JPMorganChase within AMDP (AIML Data Platforms), you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firms business objectives. 

Job responsibilities

  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
  • Works closely with product managers and data strategy professionals to advance the firms agenda in AI for Data
  • Develops secure and high-quality production code, and reviews and debugs code written by others
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
  • Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
  • Mentors more junior engineers in the team

Required qualifications, capabilities, and skills

  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Advanced Python Architecture and Development skills. Must also be familiar with developing solutions in a containerized environment
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
  • Proficient in all aspects of the Software Development Life Cycle
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Practical cloud native experience

Preferred qualifications, capabilities, and skills

  • Any background in graph databases (especially RDF stores like AWS Neptune)
  • Working familiarity with Gen AI Engineering tools/frameworks - capable of designing / building pipelines 

 

 

Lead Software Engineer within the AI/ML Data Platforms group

Lead Software Engineer – AIML Data Platform (Data, Python, Containers/Kubernetes)

Compensation

Not specified

City: London

Country: United Kingdom

J.P. Morgan logo
Bulge Bracket Investment Banks

11 days ago

No clicks

at J.P. Morgan

ExperiencedNo visa sponsorship

**Lead Software Engineer - AIML Data Platform:** Lead agile team, enhancing secure, scalable technology products. Core responsibility: design, develop, and troubleshoot AI for Data solutions using Python. Utilize containers/Kubernetes, improve code quality, drive automation, and coach junior engineers. Requires advanced Python skills, hands-on experience in SDLC, and proficiency in cloud native environments, with a plus for graph database and Gen AI Engineering backgrounds.

Full Job Description

Location: LONDON, LONDON, United Kingdom

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. 

As a Lead Software Engineer at JPMorganChase within AMDP (AIML Data Platforms), you are an integral part of an agile team that works to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. As a core technical contributor, you are responsible for conducting critical technology solutions across multiple technical areas within various business functions in support of the firms business objectives. 

Job responsibilities

  • Executes creative software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problems
  • Works closely with product managers and data strategy professionals to advance the firms agenda in AI for Data
  • Develops secure and high-quality production code, and reviews and debugs code written by others
  • Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team.
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation.
  • Identifies opportunities to eliminate or automate remediation of recurring issues to improve overall operational stability of software applications and systems
  • Leads evaluation sessions with external vendors, startups, and internal teams to drive outcomes-oriented probing of architectural designs, technical credentials, and applicability for use within existing systems and information architecture
  • Mentors more junior engineers in the team

Required qualifications, capabilities, and skills

  • Hands-on practical experience delivering system design, application development, testing, and operational stability
  • Advanced Python Architecture and Development skills. Must also be familiar with developing solutions in a containerized environment
  • Demonstrated experience leading effective use of approved AI-assisted software development tools (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security.
  • Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching engineers on safe, compliant adoption within delivery practices
  • Proficient in all aspects of the Software Development Life Cycle
  • Advanced understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
  • Practical cloud native experience

Preferred qualifications, capabilities, and skills

  • Any background in graph databases (especially RDF stores like AWS Neptune)
  • Working familiarity with Gen AI Engineering tools/frameworks - capable of designing / building pipelines 

 

 

Lead Software Engineer within the AI/ML Data Platforms group